import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


_SCREAMING_SNAKE_CASE     				=		get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
    from transformers.models.plbart.modeling_plbart import shift_tokens_right

_SCREAMING_SNAKE_CASE     				=		50_003
_SCREAMING_SNAKE_CASE     				=		50_002



@require_sentencepiece
@require_tokenizers
class 							a				(     UpperCAmelCase__			,     unittest.TestCase			):







 """simple docstring"""






 lowerCamelCase      :Tuple            =						PLBartTokenizer
 lowerCamelCase      :str            =						None
 lowerCamelCase      :Optional[Any]            =						False



 def 	UpperCAmelCase				(   self				)    ->   List[Any]:
        super().setUp()

        # We have a SentencePiece fixture for testing
        _A	  =    PLBartTokenizer(_a						,							language_codes="""base"""						,							keep_accents=_a				)
        tokenizer.save_pretrained(self.tmpdirname				)



 def 	UpperCAmelCase				(   self				)    ->   Optional[int]:
        _A	  =    PLBartTokenizer(_a						,							language_codes="""base"""						,							keep_accents=_a				)

        _A	  =    tokenizer.tokenize("""This is a test"""				)
        self.assertListEqual(_a						,							["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]				)

        self.assertListEqual(
            tokenizer.convert_tokens_to_ids(_a				)						,							[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]						,							)

        _A	  =    tokenizer.tokenize("""I was born in 92000, and this is falsé."""				)
        self.assertListEqual(
            _a						,							[
                SPIECE_UNDERLINE + """I""",
                SPIECE_UNDERLINE + """was""",
                SPIECE_UNDERLINE + """b""",
                """or""",
                """n""",
                SPIECE_UNDERLINE + """in""",
                SPIECE_UNDERLINE + """""",
                """9""",
                """2""",
                """0""",
                """0""",
                """0""",
                """,""",
                SPIECE_UNDERLINE + """and""",
                SPIECE_UNDERLINE + """this""",
                SPIECE_UNDERLINE + """is""",
                SPIECE_UNDERLINE + """f""",
                """al""",
                """s""",
                """é""",
                """.""",
            ]						,							)
        _A	  =    tokenizer.convert_tokens_to_ids(_a				)
        self.assertListEqual(
            _a						,							[
                value + tokenizer.fairseq_offset
                for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
            ]						,							)

        _A	  =    tokenizer.convert_ids_to_tokens(_a				)
        self.assertListEqual(
            _a						,							[
                SPIECE_UNDERLINE + """I""",
                SPIECE_UNDERLINE + """was""",
                SPIECE_UNDERLINE + """b""",
                """or""",
                """n""",
                SPIECE_UNDERLINE + """in""",
                SPIECE_UNDERLINE + """""",
                """<unk>""",
                """2""",
                """0""",
                """0""",
                """0""",
                """,""",
                SPIECE_UNDERLINE + """and""",
                SPIECE_UNDERLINE + """this""",
                SPIECE_UNDERLINE + """is""",
                SPIECE_UNDERLINE + """f""",
                """al""",
                """s""",
                """<unk>""",
                """.""",
            ]						,							)

        _A	  =    tokenizer.vocab_size
        _A	  =    [tokenizer.convert_ids_to_tokens(_a				) for x in range(end - 4						,							_a				)]

        self.assertListEqual(_a						,							["""__java__""", """__python__""", """__en_XX__""", """<mask>"""]				)

        _A	  =    """java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
        _A	  =    tokenizer(_a				).input_ids
        self.assertEqual(
            tokenizer.decode(_a						,							skip_special_tokens=_a						,							clean_up_tokenization_spaces=_a				)						,							_a						,							)



 def 	UpperCAmelCase				(   self				)    ->   Tuple:
        _A	  =    PLBartTokenizer(_a						,							language_codes="""multi"""						,							keep_accents=_a				)

        _A	  =    tokenizer.tokenize("""This is a test"""				)
        self.assertListEqual(_a						,							["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]				)

        self.assertListEqual(
            tokenizer.convert_tokens_to_ids(_a				)						,							[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]						,							)

        _A	  =    tokenizer.tokenize("""I was born in 92000, and this is falsé."""				)
        self.assertListEqual(
            _a						,							[
                SPIECE_UNDERLINE + """I""",
                SPIECE_UNDERLINE + """was""",
                SPIECE_UNDERLINE + """b""",
                """or""",
                """n""",
                SPIECE_UNDERLINE + """in""",
                SPIECE_UNDERLINE + """""",
                """9""",
                """2""",
                """0""",
                """0""",
                """0""",
                """,""",
                SPIECE_UNDERLINE + """and""",
                SPIECE_UNDERLINE + """this""",
                SPIECE_UNDERLINE + """is""",
                SPIECE_UNDERLINE + """f""",
                """al""",
                """s""",
                """é""",
                """.""",
            ]						,							)
        _A	  =    tokenizer.convert_tokens_to_ids(_a				)
        self.assertListEqual(
            _a						,							[
                value + tokenizer.fairseq_offset
                for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
            ]						,							)

        _A	  =    tokenizer.convert_ids_to_tokens(_a				)
        self.assertListEqual(
            _a						,							[
                SPIECE_UNDERLINE + """I""",
                SPIECE_UNDERLINE + """was""",
                SPIECE_UNDERLINE + """b""",
                """or""",
                """n""",
                SPIECE_UNDERLINE + """in""",
                SPIECE_UNDERLINE + """""",
                """<unk>""",
                """2""",
                """0""",
                """0""",
                """0""",
                """,""",
                SPIECE_UNDERLINE + """and""",
                SPIECE_UNDERLINE + """this""",
                SPIECE_UNDERLINE + """is""",
                SPIECE_UNDERLINE + """f""",
                """al""",
                """s""",
                """<unk>""",
                """.""",
            ]						,							)
        _A	  =    tokenizer.vocab_size
        _A	  =    [tokenizer.convert_ids_to_tokens(_a				) for x in range(end - 7						,							_a				)]

        self.assertListEqual(
            _a						,							["""__java__""", """__python__""", """__en_XX__""", """__javascript__""", """__php__""", """__ruby__""", """__go__"""]				)
        _A	  =    """java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
        _A	  =    tokenizer(_a				).input_ids
        self.assertEqual(
            tokenizer.decode(_a						,							skip_special_tokens=_a						,							clean_up_tokenization_spaces=_a				)						,							_a						,							)



@require_torch
@require_sentencepiece
@require_tokenizers
class 							a				(     unittest.TestCase			):







 """simple docstring"""






 lowerCamelCase      :Tuple            =						'''uclanlp/plbart-python-en_XX'''
 lowerCamelCase      :Optional[int]            =						[
     '''def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])''',
     '''def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])''',
 ]
 lowerCamelCase      :str            =						[
     '''Returns the maximum value of a b c.''',
     '''Sums the values of a b c.''',
 ]
 lowerCamelCase      :List[str]            =						[
     134,
     5452,
     33460,
     33441,
     33463,
     33465,
     33463,
     33449,
     988,
     20,
     33456,
     19,
     33456,
     771,
     39,
     4258,
     889,
     3318,
     33441,
     33463,
     33465,
     33463,
     33449,
     2471,
     2,
     PYTHON_CODE,
 ]



 @classmethod
 def 	UpperCAmelCase				(   cls				)    ->   int:
        _A	  =    PLBartTokenizer.from_pretrained(
            cls.checkpoint_name						,							language_codes="""base"""						,							src_lang="""python"""						,							tgt_lang="""en_XX"""				)
        _A	  =    1
        return cls



 def 	UpperCAmelCase				(   self				)    ->   Optional[int]:
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__java__"""]						,							5_00_01				)
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__python__"""]						,							5_00_02				)
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__en_XX__"""]						,							5_00_03				)



 def 	UpperCAmelCase				(   self				)    ->   Optional[Any]:
        _A	  =    self.tokenizer.batch_encode_plus(self.src_text				).input_ids[0]
        self.assertListEqual(self.expected_src_tokens						,							_a				)



 def 	UpperCAmelCase				(   self				)    ->   int:
        self.assertIn(_a						,							self.tokenizer.all_special_ids				)
        _A	  =    [EN_CODE, 90_37, 3_34_42, 57, 7_52, 1_53, 14, 56, 18, 9, 2]
        _A	  =    self.tokenizer.decode(_a						,							skip_special_tokens=_a				)
        _A	  =    self.tokenizer.decode(generated_ids[1:]						,							skip_special_tokens=_a				)
        self.assertEqual(_a						,							_a				)
        self.assertNotIn(self.tokenizer.eos_token						,							_a				)



 def 	UpperCAmelCase				(   self				)    ->   List[str]:
        _A	  =    ["""def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""" * 20]
        self.assertIsInstance(src_text[0]						,							_a				)
        _A	  =    10
        _A	  =    self.tokenizer(_a						,							max_length=_a						,							truncation=_a				).input_ids[0]
        self.assertEqual(ids[-2]						,							2				)
        self.assertEqual(ids[-1]						,							_a				)
        self.assertEqual(len(_a				)						,							_a				)



 def 	UpperCAmelCase				(   self				)    ->   Any:
        self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """__java__"""]				)						,							[5_00_04, 5_00_01]				)



 def 	UpperCAmelCase				(   self				)    ->   Dict:
        _A	  =    tempfile.mkdtemp()
        _A	  =    self.tokenizer.fairseq_tokens_to_ids
        self.tokenizer.save_pretrained(_a				)
        _A	  =    PLBartTokenizer.from_pretrained(_a				)
        self.assertDictEqual(new_tok.fairseq_tokens_to_ids						,							_a				)



 @require_torch
 def 	UpperCAmelCase				(   self				)    ->   Optional[Any]:
        _A	  =    self.tokenizer(self.src_text						,							text_target=self.tgt_text						,							padding=_a						,							return_tensors="""pt"""				)
        _A	  =    shift_tokens_right(batch["""labels"""]						,							self.tokenizer.pad_token_id				)

        # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
        self.assertEqual(batch.input_ids[1][-2:].tolist()						,							[2, PYTHON_CODE]				)
        self.assertEqual(batch.decoder_input_ids[1][0]						,							_a				)
        self.assertEqual(batch.decoder_input_ids[1][-1]						,							2				)
        self.assertEqual(batch.labels[1][-2:].tolist()						,							[2, EN_CODE]				)



 @require_torch
 def 	UpperCAmelCase				(   self				)    ->   Tuple:
        _A	  =    self.tokenizer(
            self.src_text						,							text_target=self.tgt_text						,							padding=_a						,							truncation=_a						,							max_length=len(self.expected_src_tokens				)						,							return_tensors="""pt"""						,							)
        _A	  =    shift_tokens_right(batch["""labels"""]						,							self.tokenizer.pad_token_id				)

        self.assertIsInstance(_a						,							_a				)

        self.assertEqual((2, 26)						,							batch.input_ids.shape				)
        self.assertEqual((2, 26)						,							batch.attention_mask.shape				)
        _A	  =    batch.input_ids.tolist()[0]
        self.assertListEqual(self.expected_src_tokens						,							_a				)
        self.assertEqual(2						,							batch.decoder_input_ids[0, -1]				)  # EOS
        # Test that special tokens are reset
        self.assertEqual(self.tokenizer.prefix_tokens						,							[]				)
        self.assertEqual(self.tokenizer.suffix_tokens						,							[self.tokenizer.eos_token_id, PYTHON_CODE]				)



 def 	UpperCAmelCase				(   self				)    ->   Any:
        _A	  =    self.tokenizer(self.src_text						,							padding=_a						,							truncation=_a						,							max_length=3						,							return_tensors="""pt"""				)
        _A	  =    self.tokenizer(
            text_target=self.tgt_text						,							padding=_a						,							truncation=_a						,							max_length=10						,							return_tensors="""pt"""				)
        _A	  =    targets["""input_ids"""]
        _A	  =    shift_tokens_right(_a						,							self.tokenizer.pad_token_id				)

        self.assertEqual(batch.input_ids.shape[1]						,							3				)
        self.assertEqual(batch.decoder_input_ids.shape[1]						,							10				)



 @require_torch
 def 	UpperCAmelCase				(   self				)    ->   str:
        _A	  =    self.tokenizer._build_translation_inputs(
            """A test"""						,							return_tensors="""pt"""						,							src_lang="""en_XX"""						,							tgt_lang="""java"""				)

        self.assertEqual(
            nested_simplify(_a				)						,							{
                # A, test, EOS, en_XX
                """input_ids""": [[1_50, 2_42, 2, 5_00_03]],
                """attention_mask""": [[1, 1, 1, 1]],
                # java
                """forced_bos_token_id""": 5_00_01,
            }						,							)










"""simple docstring"""




import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
lowerCAmelCase				:     List[str]					=				object()

# For specifying empty leaf dict `{}`
lowerCAmelCase				:     Any					=				object()



def        a__					(							snake_case__			,					snake_case__							)		->   List[Any]:
			lowerCamelCase      =   tuple((re.compile(x + """$"""							) for x in qs)							)
			for i in range(len(snake_case__							) - len(snake_case__							) + 1							):
						lowerCamelCase      =   [x.match(snake_case__							) for x, y in zip(snake_case__			,					ks[i:]							)]
						if matches and all(snake_case__							):
									return True
			return False



def        a__					(							snake_case__							)		->   str:
			def replace(snake_case__			,					snake_case__							):
						for rule, replacement in rules:
									if _match(snake_case__			,					snake_case__							):
												return replacement
						return val

			return replace



def        a__					(							)		->   Union[str, Any]:
			return [
			    # embeddings
			    (("transformer", "wpe", "embedding"), P("""mp"""			,					snake_case__							)),
			    (("transformer", "wte", "embedding"), P("""mp"""			,					snake_case__							)),
			    # atention
			    (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(snake_case__			,					"""mp"""							)),
			    (("attention", "out_proj", "kernel"), P("""mp"""			,					snake_case__							)),
			    (("attention", "out_proj", "bias"), None),
			    # mlp
			    (("mlp", "c_fc", "kernel"), P(snake_case__			,					"""mp"""							)),
			    (("mlp", "c_fc", "bias"), P("""mp"""							)),
			    (("mlp", "c_proj", "kernel"), P("""mp"""			,					snake_case__							)),
			    (("mlp", "c_proj", "bias"), None),
			    # layer norms
			    ((r"ln_\d+", "bias"), None),
			    ((r"\d+", r"ln_\d+", "scale"), None),
			    (("ln_f", "bias"), None),
			    (("ln_f", "scale"), None),
			]



def        a__					(							snake_case__							)		->   Optional[Any]:
			lowerCamelCase      =   _get_partition_rules()
			lowerCamelCase      =   _replacement_rules(snake_case__							)
			lowerCamelCase      =   {k: _unmatched for k in flatten_dict(snake_case__							)}
			lowerCamelCase      =   {k: replace(snake_case__			,					snake_case__							) for k, v in initd.items()}
			assert _unmatched not in result.values(), "Incomplete partition spec."
			return freeze(unflatten_dict(snake_case__							)							)



